3D motion segmentation and 3D localization of mobile robots using an array of static cameras and objective function minimization

2009 ◽  
Author(s):  
C. Losada ◽  
M. Mazo ◽  
S. Palazuelos ◽  
D. Pizarro ◽  
M. Marron ◽  
...  
Keyword(s):  
Mobile Robots ◽  
Objective Function ◽  
Motion Segmentation ◽  
Function Minimization ◽  
3D Motion ◽  
3D Localization

Accurate 3D Localization Using RGB-TOF Camera and IMU for Industrial Mobile Robots

Robotica ◽  
2021 ◽  
pp. 1-18
Author(s):  
Majid Yekkehfallah ◽  
Ming Yang ◽  
Zhiao Cai ◽  
Liang Li ◽  
Chuanxiang Wang
Keyword(s):  
Mobile Robots ◽  
Inertial Measurement Unit ◽  
Indoor Environment ◽  
State Of The Art ◽  
Low Cost ◽  
Estimation Algorithm ◽  
Measurement Unit ◽  
3D Localization ◽  
Fast Motion ◽  
Tof Camera

SUMMARY Localization based on visual natural landmarks is one of the state-of-the-art localization methods for automated vehicles that is, however, limited in fast motion and low-texture environments, which can lead to failure. This paper proposes an approach to solve these limitations with an extended Kalman filter (EKF) based on a state estimation algorithm that fuses information from a low-cost MEMS Inertial Measurement Unit and a Time-of-Flight camera. We demonstrate our results in an indoor environment. We show that the proposed approach does not require any global reflective landmark for localization and is fast, accurate, and easy to use with mobile robots.

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